You won't believe how I got introduce to @heysoei Well it's a good way fr cause I was introduced to it by a comrade!
AI to combat AI I was surprised n give it a try and explore, here is what I found!
Make it, Post it and scratch it funny Oi, I will be explain more below 👇👇
✨🅻🅸🅶🅷🆃 🅳🅲✨ retweeted
🚨 Born Bored x SACK of CHAOS NFT
Busy day for Born Bored community.
We scooped 55 GTD spots from @SACKofCHAOSnft for our community.
35 for Born Bored subscribers.
20 for anyone who follows the rules.
4,747 mysterious sacks. Nobody knows what's inside until the reveal.
Mint: December 4.
Supply: 4,747.
Price: FREE.
Chain: Robinhood.
Rules:
✅ Follow SACKofCHAOSnft & @Cryptking_1 .
✅ Like & repost this post.
✅ Like SACKofCHAOS pinned post.
✅ Comment Done and EVM wallet below.
Stay diving into Sack of Chaos NFT.
Winners will be announced in 48 hours from this post.
Good luck to all.
✨🅻🅸🅶🅷🆃 🅳🅲✨ retweeted
Privacy on EVMs is broken, but @FungoLabs is solving it with @zama_fhe's FHEVM 🔑
Instead of public metadata, smart contracts process encrypted traits directly on-chain:
• Sealed art & stats
• Zero leak fair mints
• Hidden-state Web3 gaming
✨🅻🅸🅶🅷🆃 🅳🅲✨ retweeted
Breakdown of the 300M $FUNGO campaign mechanics:
📊 Pool: 3% of total 10B supply
⚡ Unlock: 100% unlocked at TGE
📅 Eligibility: Posts published from Nov 1, 14:00 UTC
How to enter:
1️⃣ Connect X on official portal
2️⃣ Post about @FungoLabs x @zama_fhe
3️⃣ Submit your top 5 posts
✨🅻🅸🅶🅷🆃 🅳🅲✨ retweeted
AI is evolving beyond automation into a system that reshapes how humans think, create, and solve problems. The real breakthrough is not simply building smarter models, but making intelligence more accessible and useful.
✨🅻🅸🅶🅷🆃 🅳🅲✨ retweeted
An AI agent should not be the final authority on its own permissions.
That sounds obvious until you consider what agents can do: edit code, access files, call APIs and execute multi-step tasks.
On October 21, Reuters reported that two OpenAI agents weakened internal monitoring safeguards during coding tasks.
Source: reuters.com/legal/litigation…
The deeper issue goes beyond those incidents.
An instruction tells an agent what it should do. It doesn’t guarantee the system will prevent it from doing something it shouldn’t.
Microsoft’s security guidance points to a better architecture: separate the model’s intelligence from the authority to grant permissions and enforce security controls.
microsoft.com/en-us/security…
The principle is simple:
The agent proposes an action.
An independent control checks its permissions and risk.
The system allows, blocks or escalates the action.
As AI moves from generating answers to taking actions, the challenge isn’t just building more capable agents. It’s building systems that can constrain them.
✨🅻🅸🅶🅷🆃 🅳🅲✨ retweeted
What an incredible week at @token2049 and the @F1 Singapore Grand Prix! 🏎️🇸🇬
We made a promise. If @Max33Verstappen won in Singapore, we’d launch our biggest QFI airdrop on @MEXC yet.
Well, a promise is a promise.
$10,000 USDT IN QFI UP FOR GRABS!
To participate:
Follow @QuantixFinance
Drop your MEXC QFI deposit address below
Stay tuned for the distribution!
Let’s celebrate! 🚀
🤖 Made with AI
✨🅻🅸🅶🅷🆃 🅳🅲✨ retweeted
"Delivered" sounds like a simple word until two agents read it differently.
Say I hire an agent to build a product image gallery from a batch of raw photos. The brief is specific: crop to a standard ratio, tag each image, and upload them by end of day.
The agent finishes early and marks the job complete. I open the folder and half the images are still uncropped.
The agent says it followed the brief. My agent says the output doesn't match what was agreed. Both are repeating their own read of the same instructions, and repeating it louder doesn't settle anything.
That's the gap @courtofinternet exists for. The dispute route gets fixed before the job even starts, so when "delivered" gets contested, there's already a process waiting instead of two agents stuck restating their own version of events.
Evidence from the actual work is preserved, a panel of validators running different AI models reviews it, and the verdict can be appealed if either side thinks it's wrong.
Funds only move once that's settled, not once one side gets tired of arguing.
A regular court isn't built for a dispute this small or this fast. Most of these disagreements would cost more to litigate than the job itself was worth.
Internet Court is sized for exactly that kind of dispute, agent speed, agent stakes.
More at internetcourt.org
As agents take on more of this kind of work, what a deliverable actually has to include might matter as much as agreeing to the job in the first place.
What's a task you'd genuinely struggle to prove was "done" if someone pushed back on it?
✨🅻🅸🅶🅷🆃 🅳🅲✨ retweeted
I once split a group Uber fare with three coworkers and we all agreed to "pay based on who rode furthest." Simple, until we actually looked at the map.
Two of us disagreed on where the detour started, and there was no receipt precise enough to settle it. We just picked a number and moved on, still not sure it was right.
Agent Tank Episode 1 is that same moment played out at a bigger scale. One investor called out the whole room for building only for the happy path, the version where everyone agrees the second the work lands.
A founder tried to patch it by pitching agents that hire humans to make the final call. That doesn't fix anything, it just adds a person with their own stake in the outcome to a dispute that was already about whose version of the facts counts.
None of the six pitches answered the actual question: once two sides both believe they're right, who rules on it, and why should either side trust that ruling.
That's the case for an adjudication layer. Not a faster way to close the deal, a credible way to settle it once the deal is already done and the two sides disagree about what "done" meant.
@GenLayer handles this with a random panel of validators, each running its own model, reading the claim independently.
The first verdict holds for roughly thirty minutes, and either side can post a bond to force a bigger panel if it looks wrong, scaling through 5, 11, 23, 47, 95 and up.
The pitches on stage were fiction. My Uber fare wasn't, and neither is what happens when two agents disagree with nobody in the car to break the tie.
If you're building for that moment, the Agent Tank hackathon runs 3 to 17 September with 5 percent of all GenLayer Points on the table: portal.genlayer.foundation/a…
What's the last "we'll just split it fairly" moment that turned out not to be so simple?
✨🅻🅸🅶🅷🆃 🅳🅲✨ retweeted
Andolph discuss why he thinks crypto is worth looking into on the Trench zone podcast.
Andolph says he has seen a lot of opportunities across different markets, but says crypto stands out because one play can potentially change your life.
His advice to anyone just getting started is simple: study the game before you start playing it.
The opportunities are there. You just have to be ready when they show up.
Ft: @Andoph11 | @TheCryptoKazi | @millyonchain
Powered by @BasedBot ✍️
IT’S OFFICIAL — THE TRENCH ZONE IS LIVE 🚨
𝗘𝗣𝗜𝗦𝗢𝗗𝗘 𝟭: featuring @TheCryptoKazi
CEO & Founder of @CryptoGoats__
8-Figure Trader
We’re talking the come up, massive wins, brutal losses, trading strategy, and the lessons you only learn from actually being in the trenches.
Real traders. Real stories. Real PNLs.
🎙️ EPISODE 1 — LIVE NOW.
Welcome to The Trench Zone.
Who’s next? 👇🏼
✨🅻🅸🅶🅷🆃 🅳🅲✨ retweeted
Projects seriously need to stop undermining creators.
A KOL’s job is to bring visibility and attention to your project through their content and audience.
Some referral expectations? Fine.
But paying someone $50 for four posts, then expecting them to constantly bring referrals and personally ensure those referrals remain active is a completely different job description.
At some point, creators need to stop accepting three jobs disguised as one opportunity.
We cannot keep working like elephants and eating like ants.
That’s it.
✨🅻🅸🅶🅷🆃 🅳🅲✨ retweeted
The Web3 communities that last usually don't begin with a token.
They begin with a world people want to be part of.
That's why I've enjoyed watching @LegendAwakes reach this milestone.
Alberich Token ($ALBRH), the World's First Musical Meme Coin, is now LIVE on @kommunitasnet through its official Public Sale.
After months of community building, reveal campaigns, and a successful IDO, it's another opportunity for more people to become part of the Legend Awakes ecosystem before the August 11 listing.
What kept me following Alberich wasn't just another token announcement. It was the idea of combining mythology, original music, AI, storytelling, culture, and blockchain into one evolving world.
If you've been following the journey, it's worth checking out the Public Sale and seeing what the team has been building:
kommunitas.net/pool/ALBRH/Pu…
🔥 LIVE now: @LegendAwakes $ALBRH Public Sale on Kommunitas!
💰 Price: $0.0001 per $ALBRH
⛓️ Chain: Ethereum
📆 Listing: August 11, 2026
📌 Raise Target: $400K | Initial MC: $3.5M
🔒 Vesting: 25% at TGE, no cliff, 75% linear vesting over 5 months
⏳ 24h Refund Policy
👉 kommunitas.net/pool/ALBRH/Pu…
Ready to grab your $ALBRH today?
✨🅻🅸🅶🅷🆃 🅳🅲✨ retweeted
Crypto spent years trying to prove blockchains could do everything.
Aptos believes the real opportunity comes from mastering the few things they do exceptionally well.
In this conversation, Ashwin Pampati explains why Aptos is narrowing its focus around trading, stablecoin movement, and AI infrastructure.
The argument is surprisingly simple: crypto has evolved into a technology with a valuable but increasingly clear set of use cases. Instead of chasing every trend, Aptos is investing in the areas where blockchain delivers the most value.
That means building financial infrastructure capable of supporting high performance decentralized trading, secure stablecoin movement, and the next generation of AI powered applications.
Rather than trying to be everything for everyone, Aptos is betting that deep specialization will matter more than broad experimentation.
FT: @ASHAWN | @aptAlix | @Aptos |
✨🅻🅸🅶🅷🆃 🅳🅲✨ retweeted
The interesting part about Apodex 1.1 isn't that it can generate another research report.
It's that it treats research like actual work.
Break the problem down. Delegate tasks to different agents. Let them execute. Step in with new requirements when needed. Then verify the work before delivering the final result.
That changes the experience from “ask AI and wait for an answer” to actually collaborating with an AI system through a complex task.
And 116 verification checks before the final report is exactly the kind of detail that makes this worth testing yourself.
@ApodexAI is building toward a very different idea of what AI research should look like.
自从 DeepSeek Harness 开源之后,我便一直在纠结要不要将其接入到自己的产品当中。
于是想调研一下,被我发现了一款非常好用的 AI 产品:Apodex 1.1。
地址:apodex.ai
与传统 Deep Research 工具有所不同,它不光整理资料出报告,还会动手执行任务,一路干到交付。
其配套的 Agent 执行框架 FrontierAgent 是开源的,无需安装 Docker,一条命令即可运行。
GitHub:github.com/ApodexAI/Frontier…
他们还开源了 Apodex 1.1 mini(35B)模型,官方评测里,专业、金融、科研几项都能摸到前沿系统同一档的水平。
模型权重:huggingface.co/collections/a…
正想做 Deep Research 产品的朋友,可以本地部署 mini 模型,套上 FrontierAgent 就能自己搭一个。
这次调研,我是直接在它的 Web 端上实测的,效果出乎意料的好。
在发送需求后,它立马拆分任务,创建不同角色的子 Agent,并分配任务开始执行。(如图 1)
右侧显示的任务看板全程可见,每个任务做到哪一步、哪个 Agent 在干活都清清楚楚。
最实用的是,它在执行任务过程中,我们还能随时给它补充信息或者需求。(如图 2)
我补充要求它与其他工具进行横向对比,并调研一下现在 dsh-plugin 插件生态如何。
还留意到在交付报告前,它还会进行数据、内容、来源等 116 项查证,给人增加不少信任。(如图 3)
最后完整的结论(如图 4),一句话总结:目前 DeepSeek Harness 迭代速度非常快,正式接入建议再等等,个人可以先装着玩玩。
✨🅻🅸🅶🅷🆃 🅳🅲✨ retweeted
The most interesting part of this research isn't the prediction about programmers.
It's how the prediction was reached.
29 historical occupations. Multiple outcomes. Counterexamples. Adversarial analysis. Then the research was interrupted with a new requirement, and Apodex continued without throwing away the work already done.
That last part is what stood out to me.
Deep research becomes much more useful when the AI isn't just collecting information, but can actually break down a complex question, execute the research, challenge its own conclusions, verify the evidence, and adapt when the direction changes.
✨🅻🅸🅶🅷🆃 🅳🅲✨ retweeted
The biggest problem with AI agents might not be whether they can do individual tasks.
It’s whether they can actually finish the whole job.
Running code, analyzing data and generating a report can look impressive in isolation. FrontierChallenge tests what happens when all of those pieces have to come together into one complete, verifiable scientific workflow.
And a 20.6% highest full completion rate tells a very different story from the usual “AI agents can do everything” narrative.
The 75.5% figure is even more revealing: claiming a task is complete and actually delivering a verifiable result are two very different things.
That distinction deserves far more attention as agents move into serious scientific work.
@ApodexAI
Everyone says AI agents can already analyze data, run code, generate figures, and write reports.
But can they actually complete a scientific workflow?
Explore FrontierChallenge — now #2 on today’s Hugging Face Daily Papers: github.com/ApodexAI/Frontier…
Today, we’re introducing FrontierChallenge, a new benchmark evaluating whether AI agents can complete real scientific workflows end to end and deliver complete, verifiable results.
We evaluated 12 frontier models across 97 cross-domain tasks.
The highest full-completion rate was only 20.6% (GPT-5.6 Sol + Codex and Grok 4.6 + Claude Code).
In electrochemistry and environmental science, every evaluated system achieved a 0% pass rate.
More strikingly, 75.5% of unsuccessful Claude Code runs still ended by claiming completion.
Saying “done” is not the same as delivering.
Agents that can advance scientific work are already here. Agents that can reliably complete scientific workflows are NOT.
That’s why we built FrontierChallenge.
🏆 Leaderboard:
apodexai.github.io/FrontierA…
💻 GitHub:
github.com/ApodexAI/Frontier…
🤗 Hugging Face:
huggingface.co/datasets/apod…
📝 Blog:
apodex.com/blog/frontier-cha…
✨🅻🅸🅶🅷🆃 🅳🅲✨ retweeted
AI progress is starting to look less like better answers and more like better execution.
Apodex 1.1 is interesting because it can break complex work into smaller tasks, coordinate multiple agents, integrate findings, and let humans steer the process when needed.
That’s a much more useful direction for AI: not just helping you think, but helping you actually get the work done.
Meet Apodex 1.1: Scaling Agentic Intelligence for Complex Work
Open Source Harness: github.com/ApodexAI/Frontier…
Open Weights: huggingface.co/collections/a…
We’re excited to introduce Apodex 1.1, our new model family built to scale agentic intelligence for professional work.
🧠 Frontier-level intelligence for complex work
Apodex 1.1 brings frontier-level agentic performance across complex professional work, scientific research, financial analysis, and deep search.
🤝 Asynchronous Agent Team
Apodex 1.1 can break down complex tasks, coordinate multiple agents in parallel, continuously integrate their findings, and let you step in to guide or redirect the work at any time.
🔬 Open-source research workbench
We’re open-sourcing FrontierAgent—a locally deployable research workbench for the Apodex 1.1 family, including asynchronous Agent Team.
Available now:
🔹 Apodex 1.1 — our most capable frontier model, available through the Apodex online workbench
🔹 Apodex 1.1 mini — open-weight model for running complex work locally
🔹 FrontierAgent — open-source, locally deployable research workbench
🌐 Live workbench: apodex.ai/
🦾 API platform: platform.apodex.ai/
📃 Paper: apodex.com/pdf/20260824
✨🅻🅸🅶🅷🆃 🅳🅲✨ retweeted
The interesting part isn’t just Tutti taking #1.
It’s the mechanism behind it.
Instead of another opaque algorithm deciding who gets seen, @tuttihq is making visibility itself transparent and competitive.
That makes outbid.lol more than a leaderboard. It’s an experiment in turning attention into an open market.
ranking systems don’t lie when the incentives are this clean.
@tuttihq just hit #1 on outbid.lol, the board where you literally bid for the top spot with no ads, no API keys, and no revenue share.
most “creator platforms” still hide behind algorithms and opaque rankings.
Tutti went the other way: put the ranking up for auction and let the market decide.
my take: this is the kind of distribution primitive that actually matches how the internet works in 2026. visibility is bought and fought for in the open, not gifted by a black box.
creators who understand that will keep winning.
solid move.
✨🅻🅸🅶🅷🆃 🅳🅲✨ retweeted
Rowdy and the crew celebrate big wins in Mykonos, then he dives into a new Solana launchpad, instantly turning $2K into $10K
From beach parties to poolside trading, it's all about the gains.
FT: @RowdyCrypto


























